Search engines are an indispensable tool for organizing and presenting content found on the World Wide Web. Search engines apply algorithms to evaluate and rank web pages based on their relevance to a specific user query. While such algorithms typically consider web page content and links to other web pages, they may not take into account what topics are being discussed in social media, e.g., the subsets of the entire World Wide Web that are receiving a great deal of attention from users at any given time.
Popularity and virality are two metrics used to quantify the level of user interest in any given online content. Popularity measures how many people consume or share a web page, while virality measures how content spreads amongst users of a social network over a given period of time. It would be advantageous for a search engine to be “aware” of a given content's popularity and virality when serving results to user queries. It would also be advantageous to archive such content by date to provide a historical perspective on what has been perceived as important in the past. It would further be advantageous to provide an intuitive and powerful interface allowing the user to refine search results, retrieve, and browse content that the user should be aware of.
Accordingly, it would be desirable to provide techniques for designing a temporally aware search engine or “awareness engine” that efficiently organizes online content by popularity and virality, and effectively serves such content in response to user queries.